Regularized Kernel Discriminant Analysis (RKDA) performs linear discriminant analysis in the feature space via the kernel trick. The performance of RKDA depends on the selection o...
In this paper we investigate the fault diagnosis problem in IP networks. We provide a lower bound on the average number of probes per edge using variational inference technique pro...
Rajesh Narasimha, Souvik Dihidar, Chuanyi Ji, Stev...
We develop a new component analysis framework, the Noisy-Or Component Analyzer (NOCA), that targets high-dimensional binary data. NOCA is a probabilistic latent variable model tha...
We present new insights into how to achieve higher frequencies in large-scale nonlinear predictive control using truncated-like schemes. The basic idea is that, instead of solving ...
— Finding the k nearest neighbors (kNN) of a query point, or a set of query points (kNN-Join) are fundamental problems in many application domains. Many previous efforts to solve...